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Current status of GATK4 GermlineCNVCaller tools and best practices.

I would like to try out GATK4 for discovering or genotyping germline CNV's in a cohort of few hundred whole genome sequenced samples. I work with non-human species data, but the genome sizes are almost the same as human or smaller.

Can you give some more information about what the current status is of the GATK4 GermlineCNVCaller tools and if you have an estimation for when the best practices for these tools should be available?

It would also be nice if you can give an idea if the GATK4 GermlineCNVCallertools tools are expected to work for non-human species, e.g. other vertebrates, simple / complex plants genomes and bacteria.

Best Answers

@WimS The GermlineCNVCaller pipeline is still in beta, as we are still running evaluations so that we can determine recommendations for Best Practices parameter values. However, you are welcome to give the pipeline a try---just be aware that you may need to tune some parameters. We hope to complete evaluations in a month or so.

Alternatively, you can try running the ModelSegments pipeline. Because this pipeline simply uses PCA for denoising, it is likely that it may miss common germline events that may be in your panel of normals (if these contribute enough variance to the data, they will be picked up as principal components). For this reason, we primarily recommend the ModelSegments pipeline for somatic CNVs; however, we've seen that it is certainly sensitive enough to pick up some rare germline CNVs, as well.

In principle, the GermlineCNVCaller model should be able to handle non-human species. However, for the moment, there are still some parts of the code that are specific to human (particularly when dealing with sex genotypes). We'll keep you updated as to when this changes.

A more recent CNV tutorial using v4.0.1.1 has been posted in two parts here and here
The first part mostly recapitulates the workflow on this page, while the second part adds detection of allelic ratios.

The official workflow has algorithmic improvements to the GATK4.beta workflow illustrated here.

A newer version should be available soon. Keep an eye on the tool docs section of GATK.

@WimS The GermlineCNVCaller pipeline is still in beta, as we are still running evaluations so that we can determine recommendations for Best Practices parameter values. However, you are welcome to give the pipeline a try---just be aware that you may need to tune some parameters. We hope to complete evaluations in a month or so.

Alternatively, you can try running the ModelSegments pipeline. Because this pipeline simply uses PCA for denoising, it is likely that it may miss common germline events that may be in your panel of normals (if these contribute enough variance to the data, they will be picked up as principal components). For this reason, we primarily recommend the ModelSegments pipeline for somatic CNVs; however, we've seen that it is certainly sensitive enough to pick up some rare germline CNVs, as well.

In principle, the GermlineCNVCaller model should be able to handle non-human species. However, for the moment, there are still some parts of the code that are specific to human (particularly when dealing with sex genotypes). We'll keep you updated as to when this changes.

@Sheila Thank you! I wonder if there is a manual for GATK4 GermlineCNVCaller that I can follow? I am trying to call germline CNVs in a timely manner. It would be great if you could give me suggestions about CNV calling in terms of gatk or in general. Thanks!

Thank you @bhanuGandham . I only looked at the best practice page, which is still empty for Germline CNV. The tool documentation looks for the GermlineCNVCaller looks complete and helpful enough to get started.

I may be naive but I have to ask this question. When GermlineCNVCaller is used for whole genome samples what kind segmentation is needed for perform CNV calling accurately? Should we divide individual chromosomes into subsets in one BED file when we collect ReadCounts? I am assuming this is the case but how does the precision get affected by the divided segment lenght? Do devs have such data to share? Or instead do devs recommend structural variant calling for WGS?

Could you please let me know when the Firecloud best practice workspaces for methods "vruano-broad/GATK-gCNV-Cohort-Mode" and "vruano-broad/GATK-gCNV-Case-Mode" will be available?
I was also wondering if it is possible to provide me with access to the methods configurations associated with these on the Firecloud?
Either best practice workspace or access to the prepare configuration would greatly facilitate the analysis.

A more recent CNV tutorial using v4.0.1.1 has been posted in two parts here and here
The first part mostly recapitulates the workflow on this page, while the second part adds detection of allelic ratios.

The official workflow has algorithmic improvements to the GATK4.beta workflow illustrated here.

A newer version should be available soon. Keep an eye on the tool docs section of GATK.